Articoli correlati a A Guide to Robust Statistical Methods
Sinossi
Robust statistical methods are now being used in a wide range of disciplines. The appeal of these methods is that they are designed to perform about as well as classic techniques when standard assumptions are true—but they continue to perform well in situations where classic methods perform poorly.
This book provides a relatively non-technical guide to modern methods. The focus is on applying modern methods using R, understanding when and why classic methods can be unsatisfactory, and fostering a conceptual understanding of the relative merits of different techniques. A recurring theme is that no single method reveals everything one would like to know about the population under study. An appeal of robust methods is that under general conditions they provide much higher power than conventional techniques. Perhaps more importantly, they help provide a deeper and more nuanced understanding of data.
The book is for readers who had at least one semester of statistics, aimed at non-statisticians.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sull?autore
Rand R. Wilcox is Professor of Psychology, USC Dornsife College of Letters, Arts and Sciences. He has written 15 other statistics books, including Fundamentals of Modern Statistical Methods: Substantially Improving Power and Accuracy, 2nd edition (2010), over 400 journal articles, is a former associate editor for 5 statistics journals, is an elected member of the International Statistical Institute and he created the R package, WRS.
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Robust statistical methods are now being used in a wide range of disciplines. The appeal of these methods is that they are designed to perform about as well as classic techniques when standard assumptions are true―but they continue to perform well in situations where classic methods perform poorly.
This book provides a relatively non-technical guide to modern methods. The focus is on applying modern methods using R, understanding when and why classic methods can be unsatisfactory, and fostering a conceptual understanding of the relative merits of different techniques. A recurring theme is that no single method reveals everything one would like to know about the population under study. An appeal of robust methods is that under general conditions they provide much higher power than conventional techniques. Perhaps more importantly, they help provide a deeper and more nuanced understanding of data.
The book is for readers who had at least one semester of statistics, aimed at non-statisticians.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
- EditoreSpringer
- Data di pubblicazione2024
- ISBN 10 3031417151
- ISBN 13 9783031417153
- RilegaturaCopertina flessibile
- LinguaInglese
- Numero di pagine344
- Contatto del produttorenon disponibile
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Robust statistical methods are now being used in a wide range of disciplines. The appeal of these methods is that they are designed to perform about as well as classic techniques when standard assumptions are true-but they continue to perform well in situations where classic methods perform poorly.This book provides a relatively non-technical guide to modern methods. The focus is on applying modern methods using R, understanding when and why classic methods can be unsatisfactory, and fostering a conceptual understanding of the relative merits of different techniques. A recurring theme is that no single method reveals everything one would like to know about the population under study. An appeal of robust methods is that under general conditions they provide much higher power than conventional techniques. Perhaps more importantly, they help provide a deeper and more nuanced understanding of data.The book is for readers who had at least one semester of statistics, aimed at non-statisticians. 344 pp. Englisch. Codice articolo 9783031417153
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Robust statistical methods are now being used in a wide range of disciplines. The appeal of these methods is that they are designed to perform about as well as classic techniques when standard assumptions are true-but they continue to perform well in situations where classic methods perform poorly.This book provides a relatively non-technical guide to modern methods. The focus is on applying modern methods using R, understanding when and why classic methods can be unsatisfactory, and fostering a conceptual understanding of the relative merits of different techniques. A recurring theme is that no single method reveals everything one would like to know about the population under study. An appeal of robust methods is that under general conditions they provide much higher power than conventional techniques. Perhaps more importantly, they help provide a deeper and more nuanced understanding of data.The book is for readers who had at least one semester of statistics, aimed at non-statisticians. Codice articolo 9783031417153
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Taschenbuch. Condizione: Neu. Neuware -Robust statistical methods are now being used in a wide range of disciplines. The appeal of these methods is that they are designed to perform about as well as classic techniques when standard assumptions are true¿but they continue to perform well in situations where classic methods perform poorly.This book provides a relatively non-technical guide to modern methods. The focus is on applying modern methods using R, understanding when and why classic methods can be unsatisfactory, and fostering a conceptual understanding of the relative merits of different techniques. A recurring theme is that no single method reveals everything one would like to know about the population under study. An appeal of robust methods is that under general conditions they provide much higher power than conventional techniques. Perhaps more importantly, they help provide a deeper and more nuanced understanding of data.The book is for readers who had at least one semester of statistics, aimed at non-statisticians.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 344 pp. Englisch. Codice articolo 9783031417153
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